NCI Biomedical Informatics Blog
- Population Level Pilot: Population Information Integration, Analysis, and Modeling for Precision Surveillance
- Introducing the Data Commons Framework
- Modeling the Dynamics of Membrane-bound Mutant RAS to Accelerate Discovery of Novel Drug Targets
- CANDLE: Scaling JDACS4C Algorithms to Unprecedented Magnitudes
- Joint Design of Advanced Computing Solutions for Cancer (JDACS4C): The Right Collaboration at the Right Time to Accelerate Cancer Research
JDACS4C Cellular Level Pilot for Predictive Modeling for Pre-clinical Screening
Goal: To provide a practical, scalable approach to in silico pre-clinical screening through advances in predictive modeling.
Description: This pilot will develop machine learning, large-scale data and predictive models based on experimental biological data derived from patient-derived xenografts. This will create a feedback loop, where the experimental models inform the design of the computational models. These predictive models may also point to new targets in cancer and help identify promising new treatments. This pilot is directly aligned with the Precision Medicine Initiative in oncology in that it leverages the models to screen personalized drug treatments for individual patients.
James Doroshow (NCI, Director, Division of Cancer Treatment and Diagnosis)
Yvonne Evrard (NCI, Frederick National Laboratory for Cancer Research)
Susan Holbeck (NCI, Division of Cancer Treatment and Diagnosis)
Rick Stevens (DOE, Argonne National Laboratory)
Frank Alexander (DOE, Los Alamos National Laboratory)